FRANCE Law and Practice Contributed by: Liliana Eskenazi, Julie Ernewein and Pauline Lecrenais, Fréget Glaser et Associés
on AI outputs. Failure to do so may result in liability in the event of errors and/or harm. 10.2 Contracting and Liability Allocation Key provisions in contracts involving healthcare AI technologies include the following. • AI system description and intended use: the AI system’s intended purpose, functionality, limita - tions, and the required level of human oversight must be clearly defined. • Maintenance and updates: obligations for system maintenance, updates, and the implementation of necessary corrections to ensure continued perfor - mance and regulatory compliance must be estab - lished. • Liability allocation: clear terms on liability – such as caps on compensation – and a precise outline of cases where liability is excluded are provided. Con - tracts may also allocate shared liability – eg, the provider for system malfunctions and the health - care institution/professional for clinical decision- making. • Compliance and guarantees: the provider must guarantee that the AI complies with applicable legal and regulatory frameworks, and matches the technical documentation provided. • Technical documentation: delivery of complete and detailed technical documentation must be ensured. • Standard legal clauses: standard provisions such as insurance coverage, force majeure, applicable law, and dispute resolution mechanisms must be included. 10.3 Insurance Considerations Healthcare AI developers and users must proac - tively address several key categories of risks associ - ated with the deployment of AI technologies. These include diagnostic errors resulting from incorrect or inappropriate AI outputs, the presence of biases or malfunctions in the algorithm that may lead to unequal or unsafe outcomes, and vulnerabilities to cybersecu - rity threats that could compromise sensitive medical data or system integrity.
While no dedicated AI insurance regime currently exists, general liability frameworks apply, as follows. • Healthcare professionals are expected to carry medical malpractice insurance. • Developers must hold product liability coverage, particularly in light of the PLD. Insurers typically require robust documentation and risk manage - ment measures as prerequisites. Additionally, insurance policies must be tailored to reflect the specific regulatory environment, ethical concerns, and operational risks unique to the healthcare sec - tor, especially when AI systems are integrated into medical devices. 10.4 Best Practices for Implementation In France, the HAS included AI-related criteria in its 2025 certification framework for healthcare institu - tions (3.4-05 and 3.4-06). With regard to digital medical devices incorporating AI for professional use: • healthcare institutions are now subject to a range of obligations: mapping the use of such devices, establishing a structured process for their acquisi - tion, human control of the results, organising train - ing for healthcare professionals, etc; and • healthcare professionals have specific responsibili - ties: when using such devices, particularly for diag - nostic or therapeutic purposes, they must ensure that the patient has been informed and is made aware of the interpretation resulting from their use. 10.5 Cross-Border Considerations In addition to data transfer issues (see 6.3 Data Shar- ing and Access ), it is essential to ensure compliance for MDAI with other EU regulations, such as the AI Act and the MDR/IVDR. To this end, the Artificial Intelligence Board and the MDCG published in June 2025 the first official guid - ance document clarifying how these regulations inter - act. Key areas addressed included data governance, transparency and human oversight, accuracy, robust - ness, and cybersecurity, clinical and performance evaluation, technical documentation and post-market monitoring.
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